「decisions」の検索結果

Add fast, local, typed decisions to any project with Laya, an open-source non-generative decision model (pip install laya). It classifies, routes, scores and answers yes/no questions about a piece of text, returning calibrated probabilities in roughly 20-35 ms on a laptop GPU, with no LLM call and no data leaving the machine. Use this skill whenever the user wants to classify or route text, triage tickets or emails, detect spam, phishing, toxicity or intent, put a guardrail in front of an agent or LLM, score something against a rubric, or replace an LLM-based classifier to cut latency or cost. Also use it when they mention Laya, Jev, a "System 1 model", "typed decisions" or a "decision model", even if they never name Laya.

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Define how system components connect, establishing boundaries, patterns, and integration approaches during PRD v0.6 Architecture. Triggers on requests to design architecture, create system design, define component relationships, or when user asks "design architecture", "system design", "how do components connect?", "architecture decisions", "technical architecture", "system overview". Consumes TECH- (stack selections), RISK- (constraints), FEA- (features). Outputs ARC- entries documenting architecture decisions with rationale. Feeds v0.6 Technical Specification.

日本語の概要は準備中です。原文の説明を表示しています。

Routes, triages, flags and rates a piece of text with a probability for every option: which department or queue a ticket goes to, which intent a message expresses, whether a yes/no condition holds (is this tool call grounded, should the agent ask first, is the customer angry), and how severe or urgent it is on a rubric, each with a calibrated confidence. Runs Claude Haiku in the request and response shapes of OpenAI's Decisions API, for when no purpose-built decision model is at hand. Use for "route this ticket", "triage these", "classify with a confidence", "give me a probability that", "rate the severity", "score against this rubric", guardrail checks before a tool call, or "a Decisions API without OpenAI".

日本語の概要は準備中です。原文の説明を表示しています。

Create structured records of decisions with expected outcomes, probabilities, and quit conditions. Use for important decisions.

日本語の概要は準備中です。原文の説明を表示しています。

Facilitate a full design-thinking engagement (Empathize, Define, Ideate, Prototype, Test) grounded in real user evidence. Use whenever the user wants to understand users deeply and design a solution for them: "run design thinking", "understand our users", "design user interviews", "synthesize these interview notes", "build personas", "write How-Might-We questions", "prototype this concept", "design a usability test", "our users are churning and we don't know why", in any language ("tư duy thiết kế", "nghiên cứu người dùng", "phỏng vấn khách hàng", "デザイン思考", "设计思维"), even when they never say "design thinking". Also use when the user drops raw interview notes, transcripts, or survey exports and wants insights, personas, or product decisions. Not for "is there a market for X" desk questions (market-researcher).

Engineering ethics covering safety, professional codes of conduct, public welfare responsibility, whistleblowing, case studies (Challenger, Columbia, Hyatt Regency, Bhopal, Therac-25), and the ethical dimensions of design decisions. Includes the NSPE Code of Ethics, the iron ring tradition, risk communication, informed consent in engineering, and the duty to dissent. Use when analyzing ethical dimensions of engineering decisions, teaching professional responsibility, or reviewing designs for safety and public welfare.

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This skill should be used when the user says "lock it", "go with that", "approved", "that's the standard", or explicitly establishes a project-wide pattern like "from now on all forms should use this approach". Formalizes approved decisions into locked standards that the system enforces going forward. Not needed for story-scoped decisions — only for project-wide patterns.

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Codified expertise for returns authorization, receipt and inspection, disposition decisions, refund processing, fraud detection, and warranty claims management. Informed by returns operations managers with 15+ years experience. Includes grading frameworks, disposition economics, fraud pattern recognition, and vendor recovery processes. Use when handling product returns, reverse logistics, refund decisions, return fraud detection, or warranty claims.

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Advanced multi-agent reasoning system for complex questions requiring maximum accuracy. Uses adaptive technique selection, adversarial validation, multi-agent debate, and deep analysis. Trigger phrases "ai board", "expert panel", "deep analysis", "maximum accuracy", "thorough reasoning". Use for critical medical decisions, theological questions, philosophical analysis, complex technical problems, high-stakes decisions, or any question requiring 95%+ confidence.

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Create and manage Architecture Decision Records (ADRs). Use when making architectural changes (refactoring, API versioning, new domain layers, schema changes), when reviewing recent commits for documentation needs, or when the user mentions ADR, architecture decisions, or documenting technical decisions.

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Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when the user wants to stress-test a plan against their project's language and documented decisions.

日本語の概要は準備中です。原文の説明を表示しています。

Cross-validate code, architecture or design decisions using a second model. Use for critical decisions, complex refactoring, security reviews.

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Builds NPV, IRR, and payback models for capital investment decisions with hurdle rate calibration and risk adjustment. Use when evaluating capital investments, comparing project returns, or building capital allocation frameworks.

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Research best practices and synthesize into design decisions for artifact creation. Invoke BEFORE any creator skill to ensure research-backed decisions.

日本語の概要は準備中です。原文の説明を表示しています。

AI situational awareness — internal threat detection for hallucination risk, scope creep, and context degradation. Maps Cooper color codes to reasoning states and OODA loop to real-time decisions. Use during any task where reasoning quality matters, when operating in unfamiliar territory, after detecting early warning signs such as an uncertain fact or suspicious tool result, or before high-stakes output like irreversible changes or architectural decisions.

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Track and execute implementation work using Mighty (mt) tasks, with progress comments, linked evidence, recorded decisions, and clean closeout. Use when asked to fix a bug, implement a feature/refactor, or “work through” changes in code while keeping Mighty tasks/specs/decisions updated.

日本語の概要は準備中です。原文の説明を表示しています。

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when the user wants to stress-test a plan against the project's language and documented decisions. Run BEFORE /build on non-trivial features in repos that have (or should have) a CONTEXT.md.

日本語の概要は準備中です。原文の説明を表示しています。

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when the user wants to stress-test a plan against the project's language and documented decisions. Run BEFORE /claude-setup:build on non-trivial features in repos that have (or should have) a CONTEXT.md.

日本語の概要は準備中です。原文の説明を表示しています。

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented decisions.

日本語の概要は準備中です。原文の説明を表示しています。

"Apply pecking order theory (Myers and Majluf, 1984) to analyze how information asymmetry drives financing hierarchy decisions. Use this skill when the user needs to explain why firms prefer internal over external financing, interpret equity issuance as a negative signal, evaluate capital raising decisions, or when they ask 'why did the stock drop on the equity offering', 'should we use debt or equity', or 'why do firms hoard cash'.".

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"Solve the newsvendor problem for single-period ordering decisions under uncertain demand. Use this skill when the user needs to determine optimal order quantity for perishable goods, seasonal products, or one-time purchase decisions — even if they say 'how much to order for this season', 'perishable inventory', or 'single-period ordering'.".

日本語の概要は準備中です。原文の説明を表示しています。

Record and track organizational decisions using the RAPID framework. Captures decision context, options analysis, RAPID roles, risk assessment, and communication plan. Use when making cross-functional decisions, documenting governance choices, or building an auditable decision trail.

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Analyze system architecture, module structure, API contracts, data models, and code patterns. Use when designing systems, reviewing module boundaries, evaluating API designs, analyzing data models, checking pattern conformance, tracing decisions, or reviewing frontend architecture. Triggers: "architecture", "module design", "API design", "data model", "boundaries", "patterns", "decisions", "frontend architecture".

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Invoke a Rubber Duck Reviewer subagent to independently critique plans and implementations before proceeding. Use when the agent is about to implement a non-trivial plan (multi-file changes, architectural decisions, security-sensitive logic, database schema changes), after completing a self-contained unit of work (module, endpoint, feature), when stuck or facing repeated failures (same test fails 2+ times, unexpected results), or when the agent wants independent validation of assumptions and design decisions. Triggers on any non-trivial implementation task where independent critique would catch blind spots before they become costly mistakes.

日本語の概要は準備中です。原文の説明を表示しています。